Jena University Talk 2016.03.09 -- SQL at Zalando Technology
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Zalando, one of Europe's largest online fashion retailers, has evolved from a small Magento-based shop to a sophisticated platform using PostgreSQL and Java for its backend architecture. The company emphasizes heavy usage of stored procedures, advanced SQL features, and high availability mechanisms like Patroni and Spilo for database management. Zalando continuously explores new technologies and strategies for optimizing data management, versioning, and schema changes to support its growing operations across multiple countries.
Jena University Talk 2016.03.09 -- SQL at Zalando Technology
- 1. PostgreSQL at Zalando SQL in Fashion
- 2. About me Valentine Gogichashvili Head of Data Engineering @ZalandoTech twitter: @valgog google+: +valgog email: valentine.gogichashvili@zalando.de
- 4. 15 countries 4 fulfillment centers 15+ million active customers 2.9 billion € revenue 2015 150,000+ products 9,000+ employees One of Europe's largest online fashion retailers
- 6. Zalando Technology 900+ TECHNOLOGISTS Rapidly growing international team http://tech.zalando.de
- 7. THE HISTORY
- 8. Once upon a time... Started as a tiny online shop Prototyped on Magento (PHP) Used MySQL as a database Web Application Backend Database
- 9. REBOOT
- 10. REBOOT 5½ years ago ● Java ○ macro service architecture with SOAP as RPC layer ● PostgreSQL ○ Heavy usage of Stored Procedures ○ 4 databases + 1 sharded database on 2 shards ● Python for tooling (i.e code deploy automation)
- 11. REBOOT Java Web Frontend Java Backend PostgreSQL Java Backend PostgreSQL Java Backend PostgreSQL 9.0 RC1PostgreSQL 9.0 RC1PostgreSQL 9.0 RC1PostgreSQL "macro" services
- 12. SQL
- 13. SQL ● human readable query language ● standed the test of time ● allows automatic optimization of access to data
- 14. SQL ● window functions for moving averages etc. ● recursive SQL for searching trees and networks ● non-blocking locking ● DDL locking (schema guarantees)
- 15. PostgreSQL
- 17. PostgreSQL ● Minimal DDL locks (easy schema changes) ● Nearest neighbour searching using an index ● Block-range indexes ● Serializability (true theoretical serializability) ● JSONB - compressed JSON, fully indexable ● Data sampling with guarantees on execution time
- 18. PostgreSQL ● Read scalability: "Hot standby" replicas ● Synchronous Replication ● Cascading Replication ● Logical Decoding to allow Change Data Capture ● BDR for Multi-Master Scalability ● Write scalability/sharding (is on the way)
- 19. PostgreSQL ● Multiple data models (tables, JSON, ROWs, arrays) ● ACID ● Eventual Consistency (on-demand)
- 21. Stored Procedures ● clean transaction scope ● very clean data ● processing close to data ● no need in classical ORM mappers
- 22. Stored Procedures ● no debugger in Eclipse or IntelliJ ● difficult for projects heavy on CRUD ● versioning automation is needed
- 23. Stored Procedures Java Sproc Wrapper ● very easy to use ● proxies stored procedures as Java method calls ● supports complex type mapping ● supports transparent sharding
- 24. Stored Procedures CREATE FUNCTION register_customer(p_email text, p_gender z_data.gender) RETURNS int AS $$ INSERT INTO z_data.customer (c_email, c_gender) VALUES (p_email, p_gender) RETURNING c_id $$ LANGUAGE 'sql' SECURITY DEFINER; SQL
- 25. Stored Procedures @SProcService public interface CustomerSProcService { @SProcCall int registerCustomer(@SProcParam String email, @SProcParam Gender gender); } JAVA CREATE FUNCTION register_customer(p_email text, p_gender z_data.gender) RETURNS int AS $$ INSERT INTO z_data.customer (c_email, c_gender) VALUES (p_email, p_gender) RETURNING c_id $$ LANGUAGE 'sql' SECURITY DEFINER; SQL
- 26. Stored Procedures @SProcService public interface CustomerSProcService { @SProcCall int registerCustomer(@SProcParam String email, @SProcParam Gender gender); } CREATE FUNCTION register_customer(p_email text, p_gender z_data.gender) RETURNS int AS $$ INSERT INTO z_data.customer (c_email, c_gender) VALUES (p_email, p_gender) RETURNING c_id $$ LANGUAGE 'sql' SECURITY DEFINER; SQL JAVA
- 27. Stored Procedures @SProcCall List<Order> findOrders(@SProcParam String email); JAVA CREATE FUNCTION find_orders(p_email text, OUT order_id int, OUT order_created timestamptz, OUT shipping_address order_address) RETURNS SETOF record AS $$ SELECT o_id, o_created, ROW(oa_street, oa_city, oa_country)::order_address FROM z_data."order" JOIN z_data.order_address ON oa_order_id = o_id JOIN z_data.customer ON c_id = o_customer_id WHERE c_email = p_email $$ LANGUAGE 'sql' SECURITY DEFINER; SQL
- 28. Stored Procedures CREATE FUNCTION find_orders(p_email text, OUT order_id int, OUT order_created timestamptz, OUT shipping_address order_address) RETURNS SETOF record AS $$ SELECT o_id, o_created, ROW(oa_street, oa_city, oa_country)::order_address FROM z_data."order" JOIN z_data.order_address ON oa_order_id = o_id JOIN z_data.customer ON c_id = o_customer_id WHERE c_email = p_email $$ LANGUAGE 'sql' SECURITY DEFINER; @SProcCall List<Order> findOrders(@SProcParam String email); JAVA SQL
- 29. Stored Procedures @SProcCall int registerCustomer(@SProcParam @ShardKey CustomerNumber customerNumber, @SProcParam String email, @SProcParam Gender gender); @SProcCall Article getArticle(@SProcParam @ShardKey Sku sku); @SProcCall(runOnAllShards = true, parallel = true) List<Order> findOrders(@SProcParam String email); JAVA JAVA JAVA
- 30. Stored Procedures Virtual Shard IDs (pre-sharding) 0 1 0 1 1 0 0 1 7 6 4 3 2 1 05 md5(partitioning_key) SprocWrapper PostgreSQL 9.0 RC1PostgreSQL 9.0 RC1PostgreSQL 9.0 RC1PostgreSQL Java Application
- 31. Stored Procedures Schema based stored procedure versioning ● uses search_path on the clients ● new schema for every application version ● automated deployments
- 33. Stored Procedures Database Tables api_v16_01 search_path = api_v16_01, public;
- 34. Stored Procedures Database Tables api_v16_01api_v16_02 search_path = api_v16_01, public;
- 35. Stored Procedures Database Tables api_v16_01api_v16_02 search_path = api_v16_02, public; search_path = api_v16_01, public;
- 36. Stored Procedures Database Tables api_v16_01api_v16_02 search_path = api_v16_02, public;
- 37. Stored Procedures Database Tables api_v16_01api_v16_02 search_path = api_v16_02, public;
- 38. Stored Procedures Database Tables api_v16_02 search_path = api_v16_02, public;
- 42. Schema management DBDIFF database schema management ● schema changes must be documented ● atomic changes per feature ● locks should be minimal
- 43. Schema management BEGIN; SELECT _v.register_patch('ZEOS-15430.order'); CREATE TABLE z_data.order_address ( oa_id int SERIAL, oa_country z_data.country, oa_city varchar(64), oa_street varchar(128), ... ); ALTER TABLE z_data."order" ADD o_shipping_address_id int REFERENCES z_data.order_address (oa_id); COMMIT; DBDIFF SQL
- 44. Schema management BEGIN; SELECT _v.register_patch('ZEOS-15430.order'); i order/database/order/10_tables/10_order_address.sql ALTER TABLE z_data."order" ADD o_shipping_address_id int REFERENCES z_data.order_address (oa_id); COMMIT; DBDIFF SQL
- 45. Schema management BEGIN; SELECT _v.register_patch('ZEOS-15430.order'); i order/database/order/10_tables/10_order_address.sql SET statement_timeout TO '3s'; ALTER TABLE z_data."order" ADD o_shipping_address_id int REFERENCES z_data.order_address (oa_id); COMMIT; DBDIFF SQL
- 46. Schema management pg_view (https://github.com/zalando/pg_view) ● helps to monitor locks and load in real-time ● used during all DB schema change rollouts nice_updater (https://github.com/zalando/acid-tools) ● runs big migrations controlling database/system load ● used during automatic data migrations
- 49. High Availability Patroni - High Availability Runner ● etcd or ZooKeeper for master election Spilo - PostgreSQL AWS appliance ● Zalando Patroni for High Availability ● Docker for packaging ● Zalando STUPS for audit compliance
- 50. Monitoring: ZMON
- 51. Open Source at Zalando Technology ● Tech Blog of Zalando Technology ● https://zalando.github.io/ - Open Source Projects ○ Java Sproc Wrapper ○ PGObserver ○ pg_view ○ Patroni ○ Spilo ○ ...
- 52. Questions?
- 53. Where to Find Us: Tech Blog: tech.zalando.com GitHub: github.com/zalando Twitter: @ZalandoTech Instagram: zalandotech Jobs: http://tech.zalando.com/jobs